Development of a Real-Time Web-Based Dashboard for Monitoring Air Quality and Light Intensity in Oyster Mushroom Cultivation

Abstract

Environmental monitoring in oyster mushroom (Pleurotus ostreatus) cultivation is still predominantly conducted manually, limiting rapid responses to environmental changes and reducing operational efficiency. This study aimed to develop and evaluate a real-time web-based dashboard capable of monitoring air quality (CO?) and light intensity in oyster mushroom cultivation environments using Internet of Things (IoT) technology. The system employed a three-layer architecture consisting of NodeMCU ESP32 sensor devices integrated with MQ135 and BH1750 sensors, an API-based communication and database layer, and a web-based visualization interface. System performance was evaluated through response-time testing, sensor accuracy assessment, and usability evaluation involving cultivation operators. The results demonstrated that the dashboard achieved low-latency visualization with an average response time of approximately 1.1 seconds, while sensor accuracy exceeded 98% for both CO? and light intensity measurements. Usability testing also indicated that the dashboard interface effectively supported environmental monitoring and operational decision-making. The study contributes theoretically to precision agriculture literature by integrating real-time environmental monitoring with user-centered visualization design and contributes practically by providing a scalable monitoring framework for smart mushroom cultivation systems. These findings indicate that web-based real-time dashboards can enhance operational efficiency, environmental awareness, and data-driven decision-making in precision agriculture.